”After the game Kasparov shocked many people on the MSN forum, which was kept open after multiple requests, by announcing he had been reading the World Team strategy board during the game.”
⇒ one could argue this was “the World, including Kasparov versus the World, excluding Kasparov”
Well only if he also posted his best ideas for how to beat himself. It's Kasparov vs the world and Kasparov cheated a bit.
Literally reading all the thoughts of your opponent is a little more than "cheating a bit". It is putting your opponent on your side of the table.
With all due respect to Barcot, Felecan, Krush, and Paehtz, it would’ve been highly unlikely that without the aid of engines, they would’ve had a close game against Kasparov. Barcot is easily the most accomplished out of these players, and by 2001 (the earliest available data) he was still “only” a 2600 player. In 1999, Kasparov was still a 2800 player at the peak of his powers. None of those 4 players would’ve stood a chance against Deep Junior, an engine used by both sides.
Had Kasparov gone out and purchased the best computer hardware at the time, and had it run analysis 24/7, would that have been cheating?
The article alludes to the fact that in 1996 Karpov crushed another World Team. I would argue that the development of competent chess engines during the period between the two matches is a key reason why the World team fared much better the second time.
Chess is a game of perfect information. Here, what Garry did can be best characterized as a “shortcut”. If he had run an engine 24/7, it would’ve produced moves better than what the World team played.
The most rigorous experiment I've seen performed, tested a group of reddit users on estimating lines in an image . Some expert individuals were far more accurate than the group average.
"The classic wisdom-of-the-crowds finding involves point estimation of a continuous quantity. This has contributed to the insight in cognitive science that a crowd's individual judgments can be modeled as a probability distribution of responses with the median centered near the true value of the quantity to be estimated." 
Notice that the term said nothing about adversarial games and or games which have moves.
A better model for those types of games is the experts' problem / multiplicative weights algorithm -- where the solution consists of a weighted plurality which is updated every turn. 
This sort doesn't prove nothing about "Wisdom of the Crowds" because the wording is too broad. But it is evidence that crowd can outperform the best individual at least theoretically. The worst mistake the crowd had made was openness of dicussion allowing Kasparov to read this discussion. It gave him the advantage and by his own words it was cruicial advantage to win.
Chess is the good candidate for hive-mind, because it is computational task which can be parallelized. You can hire tons of minds, and made them to solve different parts of the common task. There was some issues with management with mind-resources, the worst at the end-game, when many people lost their faith and started to discuss not a next move, but what is wrong with hive-mind.
> The most rigorous experiment I've seen performed, tested a group of reddit users on estimating lines in an image . Some expert individuals were far more accurate than the group average.
I'm not convinced by this. There are few objections.
1. There was no discussion between elements of hive-mind. So the abilities of hive-mind remains unused.
2. Suspicious statistics.
a. The articles compares estimates of individuals with estimates of hive-mind. Hive-mind have one set of answers, while answers of individuals are combined with knowledge of true answer. There are no example of individual outperforming hive-mind on all four data points at once.
b. There are no attempt to estimate probability to get top individual answers by chance. Maybe those selected individuals are no better than average person, but just lucky ones?
3. There are different tasks. Different tasks needs different data processing, different data processing needs different processors. For example, there are tasks that benefits from parallelizing, and there are tasks that do not. Here we come close to (1): if you want hive-mind to outperform individual, you need to find a way how to use superpowers of hive-mind with this task.
In fact, communication between crowd members in many cases significantly reduces the quality of the answers. This has been clearly demonstrated in studies of group brainstorming, where the number and quality of ideas is significantly better when group members come up with ideas independently and pool them at the end than when they come up with ideas together.
They had a marketplace for ad campaigns with Google. Instead of running ad campaigns or using artificial intelligence, a pool of optimizers would work on a campaign and Trada worked as the middle man between optimizers and advertisers.
The Trada logo was a jar of jelly beans: (http://wisdomofcrowds.blogspot.nl/2009/12/jelly-bean-experim...)
> A classic demonstration of group intelligence is the jelly-beans-in-the-jar experiment, in which invariably the group’s estimate is superior to the vast majority of the individual guesses. When finance professor Jack Treynor ran the experiment in his class with a jar that held 850 beans, the group estimate was 871. Only one of the fifty-six people in the class made a better guess.
When advertising on Google competition leads to higher prices. For example the keywords "dui lawyer" cost a fortune because the rate of return is so high for each click. Theoretically a creative individual could come up with a set of untapped, low price keywords that could lead to an effective ad campaign at a lower price.
In practice the company had major problems. Incompetent optimizers would chew through a whole budget, leading to advertiser churn, and a lot of intervention. Eventually everything becomes micro-managed which isn't a sustainable business model. (There's a reason agencies target big ad campaigns... its the only way to make it worth it because of the amount of resources you have to invest)
So there's a single data point where the wisdom of the crowds failed.
An expert would've made better decisions.
I think the wisdom of the crowd can sometimes be effective, but there are a lot of ways it can go wrong. Some things I was thinking of:
1. the crowd wasn't big enough
2. the time frame was too short to be effective
3. the heuristic was too complex or poorly tuned to lead to a good outcome
4. creative endeavors with high rates of failure lack enough signal to properly optimize (a strategy might look terrible till it suddenly works)
5. misaligned incentives undermine the goal
To illustrate the last case, in high school I had a teacher tell us that he would scale the test by the highest score. For example a 95 would give 100 and +5 to every other score in the class. With incentives like that, if everyone in the class answered no questions, everyone would get 100. (but then all it would take would be one individual to screw the whole class)
Crowds are complex, difficult to understand and hard to predict.
"Since Dec. 1 2018 (sic), the MP has been on the "right" side of 50% every single time, and (in a more meaningful measure) has a mean Brier of 0.048. (Though those are both about to be spoiled by the NASA-LISA question, probably.)" 
You can compare metaculus vs. community predictions at . The corresponding community score would be 0.119 during the same time.
that being said, democracy often leads to wishes that nobody could execute. after all, it's about what participants want, not what they really need.
- the stock market
They beat technocratic efforts every time.
 - https://www.youtube.com/user/AGADMATOR
Highest vote count amongst N players decides move choice. Player votes can even be weighted by "success" based on past performance.
But rather than chess, which is a fully deterministic, perfect information game. I'd really like to apply it to stochastic games. And see how adept crowds can be at finding an equilibria.
Pretty sure your phone is more powerfully than any human that has or might exist at chess.
Fairly sure humans can no longer assist a computer (human + computer <= computer)
So not really sure what you'd prove today?
It was also pre-lulz. The hive mind these days has seen the value in humor over original intentions.
Nice to see it's survived for so long.
The problem with the Wikipedia article is the subjectivity of how the "?" and "!" annotations on the moves are handed out - sometimes they are quite wrong.
The clearest example in the article is the fact that 37... e6 loses and thus it deserves a double question mark, because 37... e5 draws. Anybody who downloads Stockfish and the six piece table bases can see that very quickly in 2018, but I suppose Wikipedia requires an "authoritative" published source on that before it can go into the article. Similarly on the next move, 38. Rd1 wins, whereas Kasparov's 38. h6 only draws. So that also deserves at least a question mark. (perhaps Chessbase should do an article on it)
Other dubious annotations are 18... f5 when 18... Bd4 is a clear draw (also in the Kasparov and King book) and perhaps 26... f4 when 26... Bc5 was better (in "Reinventing Discovery" the author writes about this move choice quite a bit).
For example, Mikhail Tal’s made multiple sacrifices that won him games even today get a ! annotation from reviewers, even though they aren’t optimal (https://www.chess.com/forum/view/general/how-should-one-go-a...)
In a riot sparked by a chariot race, half of Constantinople was destroyed.